Publications

5. Behling, R., Bello-Cruz, Y., Iusem, A., Liu, D., & Santos, L.-R. (2026, February). On circumcentered direct methods for monotone variational inequality problems (arXiv:2506.17814). arXiv. https://doi.org/10.48550/arXiv.2506.17814

4. Behling, R., Bello-Cruz, Y., Santos, L.-R., & Silva, P. J. S. (2025). Basis pursuit by inconsistent alternating projections (arXiv:2508.15026). arXiv. https://doi.org/10.48550/arXiv.2508.15026

3. Barros, P., Behling, R., Guigues, V., & Santos, L.-R. (2025). Parallelizing the Circumcentered-Reflection Method (In Progress arXiv:2505.17258). arXiv. https://doi.org/10.48550/arXiv.2505.17258

2. Behling, R., Bello-Cruz, Y., Iusem, A. N., Ribeiro, A. A., & Santos, L.-R. (2024). Fejér* monotonicity in optimization algorithms (arXiv:2410.08331). arXiv. https://doi.org/10.48550/arXiv.2410.08331

1. Villas-Bôas, F. R., Santos, L.-R., & Oliveira, A. R. L. (2023). An Interior Point Method with no centrality parameter [In Progress].

20. Chu, Y.-C., Santos, L.-R., & Udell, M. (2026). Randomized Nyström Preconditioned Interior Point-Proximal Method of Multipliers. SIAM Journal on Scientific Computing, 48(1), A132–A159. https://doi.org/10.1137/24M1654968

19. Pamplona, J. V., Pinheiro, M. E., & Santos, L.-R. (2026). Constructing Magic Squares: An integer linear programming model and a fast approach. Computational and Applied Mathematics. Accepted. https://arxiv.org/abs/2504.20017

18. Behling, R., Bello-Cruz, Y., Iusem, A., Liu, D., & Santos, L.-R. (2024). A Finitely Convergent Circumcenter Method for the Convex Feasibility Problem. SIAM Journal on Optimization, 34(3), 2535–2556. https://doi.org/10.1137/23M1595412

17. Behling, R., Bello-Cruz, Y., Iusem, A. N., & Santos, L.-R. (2024). On the centralization of the circumcentered-reflection method. Mathematical Programming, 205, 337–371. https://doi.org/10.1007/s10107-023-01978-w

16. Behling, R., Bello-Cruz, Y., Iusem, A., Liu, D., & Santos, L.-R. (2024). A successive centralized circumcenter reflection method for the convex feasibility problem. Computational Optimization and Applications, 87(1), 83–116. https://doi.org/10.1007/s10589-023-00516-w

15. Filippozzi, R., Gonçalves, D. S., & Santos, L.-R. (2023). First-order methods for the convex hull membership problem. European Journal of Operational Research, 306(1), 17–33. https://doi.org/10.1016/j.ejor.2022.08.040

14. Arefidamghani, R., Behling, R., Iusem, A. N., & Santos, L.-R. (2023). A circumcentered-reflection method for finding common fixed points of firmly nonexpansive operators. Journal of Applied and Numerical Optimization, 5(3), 299–320. https://doi.org/10.23952/jano.5.2023.3.02

13. Behling, R., Bello-Cruz, Y., Lara-Urdaneta, H., Oviedo, H., & Santos, L.-R. (2023). Circumcentric directions of cones. Optimization Letters, 17, 1069–1081. https://doi.org/10.1007/s11590-022-01923-4

12. Araújo, G. H. M., Arefidamghani, R., Behling, R., Bello-Cruz, Y., Iusem, A., & Santos, L.-R. (2022). Circumcentering approximate reflections for solving the convex feasibility problem. Fixed Point Theory and Algorithms for Sciences and Engineering, 2022(1), 30. https://doi.org/10.1186/s13663-021-00711-6

11. Loução Jr., F. L., Mathias, M. S., Sagastizábal, C., Santos, L.-R., & Sobral, F. N. C. (2021, October 1). Hydro-reservoir management and unit-commitment in energy optimization. Mathematics in Industry Reports. VI Brazilian Study Group with Industry. https://doi.org/10.33774/miir-2021-6qw7r

10. Arefidamghani, R., Behling, R., Bello-Cruz, Y., Iusem, A. N., & Santos, L.-R. (2021). The circumcentered-reflection method achieves better rates than alternating projections. Computational Optimization and Applications, 79(2), 507–530. https://doi.org/10.1007/s10589-021-00275-6

9. Behling, R., Bello-Cruz, Y., & Santos, L.-R. (2021). Infeasibility and error bound imply finite convergence of alternating projections. SIAM Journal on Optimization, 31(4), 2863–2892. https://doi.org/10.1137/20M1358669

8. Behling, R., Bello-Cruz, Y., & Santos, L.-R. (2021). On the Circumcentered-Reflection Method for the Convex Feasibility Problem. Numerical Algorithms, 86, 1475–1494. https://doi.org/10.1007/s11075-020-00941-6

7. Behling, R., Bello-Cruz, Y., & Santos, L.-R. (2020). The block-wise circumcentered–reflection method. Computational Optimization and Applications, 76(3), 675–699. https://doi.org/10.1007/s10589-019-00155-0

6. Bueno, L. F., Haeser, G., & Santos, L.-R. (2020). Towards an efficient augmented Lagrangian method for convex quadratic programming. Computational Optimization and Applications, 76(3), 767–800. https://doi.org/10.1007/s10589-019-00161-2

5. Santos, L.-R., Villas-Bôas, F. R., Oliveira, A. R. L., & Perin, C. (2019). Optimized choice of parameters in interior-point methods for linear programming. Computational Optimization and Applications, 73(2), 535–574. https://doi.org/10.1007/s10589-019-00079-9

4. Behling, R., Bello-Cruz, Y., & Santos, L.-R. (2018). Circumcentering the Douglas–Rachford method. Numerical Algorithms, 78(3), 759–776. https://doi.org/10.1007/s11075-017-0399-5

3. Behling, R., Bello-Cruz, Y., & Santos, L.-R. (2018). On the linear convergence of the circumcentered-reflection method. Operations Research Letters, 46(2), 159–162. https://doi.org/10.1016/j.orl.2017.11.018

2. Siqueira, A. S., Silva, R. C. da, & Santos, L.-R. (2016). Perprof-py: A Python Package for Performance Profile of Mathematical Optimization Software. Journal of Open Research Software, 4(e12), 5. https://doi.org/10.5334/jors.81

1. Santos, L.-R., & Bassanezi, R. C. (2009). Sistemas P-fuzzy Unidimiensionais com Condição Ambiental. Biomatemática, 19(1), 11–24. http://www.ime.unicamp.br/~biomat/bio19_art2.pdf

6. Filippozzi, R., Gonçalves, D. S., & Santos, L.-R. (2023). Accelerating the Spherical Triangle Algorithm for the Convex-Hull Membership Problem. 4. https://www.siam.org/Portals/0/Conferences/OP/OP23_ABSTRACTS.pdf

5. Filippozzi, R., Gonçalves, D. S., & Santos, L.-R. (2022). First-order methods for the convex-hull membership problem and applications. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, 9. https://proceedings.sbmac.emnuvens.com.br/sbmac/article/view/3910

4. Ertel, P. C. R., & Santos, L.-R. (2021). Otimização e análise teórica das máquinas de vetores suporte aplicadas à classificação de dados. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, 8. https://proceedings.sbmac.org.br/sbmac/article/view/135598

3. Silva, T. da, & Santos, L.-R. (2021). Métodos iterativos para solução de sistemas lineares: aceleração usando reflexões circuncentradas. Proceeding Series of the Brazilian Society of Computational and Applied Mathematics, 8. https://proceedings.sbmac.emnuvens.com.br/sbmac/article/view/136002

2. Villas-Bôas, F. R., Oliveira, A. R. L., Perin, C., & Santos, L.-R. (2012). Polynomial Inequality Systems in Neighborhoods of the Central Path. Proceedings of the 3rd IMA Conference on Numerical Linear Algebra and Optimisation, 26.

1. Santos, L.-R., Villas-Bôas, F. R., Oliveira, A. R. L., & Perin, C. (2011). On a Polynomial Merit Function for Interior Point Methods. Proceedings of the 19th Triennial Conference of the International Federation of Operational Research Societies, 121.

3. Santos, L.-R. (2014). Optimized choice of parameters in interior-point methods for linear programming [PhD's thesis (in portuguese), IMECC/Unicamp]. https://doi.org/10.47749/T/UNICAMP.2014.931062

2. Santos, L.-R. (2008). Strategies for pests control: p-fuzzy systems and hybrid control [Master's thesis (in portuguese), IMECC/Unicamp]. https://doi.org/10.47749/T/UNICAMP.2008.434021

1. Santos, L.-R. (2004). Reconhecimento de faces utilizando pré-processamento através da transformada log-radon [Graduate dissertation (in portuguese), Universidade Regional de Blumenau]. https://bu.furb.br/consulta/portalConsulta/recuperaMfnCompleto.php?menu=rapida&CdMFN=271220